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A note's relevance is now its best chunk's similarity, everywhere: - semantic_search_notes keeps the indexed raw-distance top-k and over-fetches chunk rows (x4, composing with the x3 supersession over-fetch), then collapses to first-appearance-per-note — rows arrive distance-ordered, so first is best. Every ranked consumer (MCP/REST search, Browse, auto-inject, write-path, gate) inherits through the one function. - list_notes semantic q swaps its join for a correlated MIN-distance subquery — the join would have repeated a long note once per matching chunk and made total count chunks. - the duplicate report groups its self-join by note pair on MIN(distance): pair similarity = closest chunk pair, and the < join now also drops cross-chunk self-pairs that would flag every long note against itself. - the write gate queries once per chunk of the candidate (capped at 8), so a note duplicating an existing record in ONE SECTION is caught — the whole-document query diluted exactly the section that mattered. Integration test now seeds a two-chunk note and pins the collapse against real pgvector. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01UaYUaouG9jjhATyuxCKrQs
261 lines
9.6 KiB
Python
261 lines
9.6 KiB
Python
"""chunk_document — the document shape a record is embedded as (#280).
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The model window is 512 tokens and fastembed truncates silently, so before
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chunking, everything past ~400 words of a record was PERMANENTLY invisible to
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semantic search. These tests pin the two halves of the fix's contract: short
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records keep the exact historical shape (the corpus's sharpest vectors are
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untouched), and long records lose NOTHING — every line of the body lands in
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some chunk, each chunk inside the window budget, each carrying the title as
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its topical anchor.
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"""
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from scribe.services.embeddings import (
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_CHUNK_CHAR_BUDGET,
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chunk_document,
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embedding_text,
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)
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def _long_section(tag: str, paragraphs: int = 6, sentence: str = None) -> str:
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sentence = sentence or f"This paragraph discusses {tag} in useful detail."
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para = " ".join([sentence] * 6)
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return "\n\n".join(f"{para} (p{i})" for i in range(paragraphs))
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# --- the identity half: short records are byte-for-byte unaffected -----------
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def test_a_short_record_yields_exactly_the_historical_shape():
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"""Snippets and reference notes are the sharpest records in the corpus
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(#2485) precisely because of this shape — chunking must not touch them."""
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assert chunk_document("A title", "A short body") == [
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embedding_text("A title", "A short body")
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]
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def test_a_bodyless_record_is_one_chunk_of_its_title():
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assert chunk_document("Just a title", "") == ["Just a title"]
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def test_an_empty_record_yields_no_chunks():
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"""Callers gate on falsiness to skip embedding entirely."""
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assert chunk_document("", "") == []
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assert chunk_document(None, None) == []
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def test_a_record_exactly_at_budget_stays_whole():
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body = "x" * (_CHUNK_CHAR_BUDGET - len("T\n"))
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assert chunk_document("T", body) == [embedding_text("T", body)]
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# --- the no-lost-data half: this is what the build is FOR --------------------
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def test_every_line_of_a_long_body_lands_in_some_chunk():
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"""The point of #280. Before chunking, a 2,000-word dev-log's last three
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quarters could not influence retrieval at all. Nothing may be dropped."""
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sections = [
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f"## Topic {i}\n\n{_long_section(f'topic-{i}')}" for i in range(8)
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]
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body = "Intro paragraph before any heading.\n\n" + "\n\n".join(sections)
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chunks = chunk_document("A very long dev-log", body)
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assert len(chunks) > 1
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joined = "\n".join(chunks)
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for line in body.splitlines():
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if line.strip():
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assert line.strip() in joined, f"content dropped: {line[:60]!r}"
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def test_every_chunk_fits_the_window_budget():
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body = "\n\n".join(_long_section(f"t{i}") for i in range(10))
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for chunk in chunk_document("T", body):
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assert len(chunk) <= _CHUNK_CHAR_BUDGET + len("T") + 1
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def test_every_chunk_is_anchored_by_the_title():
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"""Each vector must carry its own topical anchor — the property that makes
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snippets discriminative. An unanchored mid-document chunk would embed as
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free-floating prose about nothing in particular."""
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body = "\n\n".join(
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f"## Section {i}\n\n{_long_section(f'sec-{i}')}" for i in range(6)
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)
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chunks = chunk_document("Retrieval reference", body)
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assert len(chunks) > 1
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for chunk in chunks:
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assert chunk.startswith("Retrieval reference\n")
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# --- boundary behaviour ------------------------------------------------------
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def test_sections_split_at_markdown_headings_and_stay_whole_when_they_fit():
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a = "## Alpha\n\nShort alpha content."
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b = "## Beta\n\n" + _long_section("beta")
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c = "## Gamma\n\n" + _long_section("gamma")
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chunks = chunk_document("T", f"{a}\n\n{b}\n\n{c}")
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# Beta's content never shares a chunk with Gamma's heading-onward content:
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# heading boundaries are chunk boundaries unless merging small sections.
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for chunk in chunks:
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assert not ("(p5)" in chunk and "## Gamma" in chunk and "beta" in chunk)
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def test_small_adjacent_sections_merge_instead_of_each_spending_a_vector():
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body = (
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"\n\n".join(f"## S{i}\n\nTiny." for i in range(4))
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+ "\n\n## Big\n\n"
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+ _long_section("big", paragraphs=10)
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)
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chunks = chunk_document("T", body)
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tiny_chunks = [c for c in chunks if "Tiny." in c]
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assert len(tiny_chunks) == 1, "four tiny sections should share one chunk"
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def test_a_heading_inside_a_code_fence_does_not_split():
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"""A commented `# step` in a recorded shell snippet is content, not
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structure."""
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body = "Intro.\n\n```bash\n# not a heading\necho hi\n```\n\nOutro."
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chunks = chunk_document("T", body)
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assert chunks == [embedding_text("T", body)]
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def test_pieces_subsplit_from_one_section_repeat_its_heading():
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"""'Which part of which topic' must survive the split — a continuation
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piece without its heading embeds as context-free prose."""
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body = "## The Only Topic\n\n" + _long_section("only", paragraphs=40)
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chunks = chunk_document("T", body)
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assert len(chunks) > 1
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for chunk in chunks:
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assert "## The Only Topic" in chunk
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def test_a_monster_single_paragraph_is_hard_split_not_dropped():
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body = "word " * 2000 # one paragraph, no newlines to split at
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chunks = chunk_document("T", body)
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assert len(chunks) > 1
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total_words = sum(chunk.count("word") for chunk in chunks)
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assert total_words == 2000
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# --- the read path: best chunk wins (#280 step 4) ----------------------------
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async def test_search_collapses_chunk_rows_to_best_chunk_per_note():
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"""Rows arrive at CHUNK grain ordered by distance; a note appearing via
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several chunks must come back ONCE, scored by its best chunk — otherwise a
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long record fills the top-k with copies of itself."""
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from unittest.mock import AsyncMock, MagicMock, patch
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from scribe.services import embeddings as emb
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note_a, note_b = MagicMock(id=1), MagicMock(id=2)
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rows = [(note_a, 0.10), (note_b, 0.20), (note_a, 0.25), (note_a, 0.30)]
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result = MagicMock()
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result.all.return_value = rows
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session, ctx = _session_ctx()
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session.execute = AsyncMock(return_value=result)
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with (
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patch.object(emb, "async_session", return_value=ctx),
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patch.object(emb, "get_embedding", AsyncMock(return_value=[0.0] * 384)),
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):
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out = await emb.semantic_search_notes(
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1, "a query", limit=8, demote_superseded=False
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)
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assert [note.id for _s, note in out] == [1, 2]
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assert out[0][0] == 1.0 - 0.10 # the BEST chunk's score, not a later one
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# --- the write path: one row per chunk (#280 step 3) -------------------------
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def _session_ctx():
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from unittest.mock import AsyncMock, MagicMock
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session = MagicMock()
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session.execute = AsyncMock()
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session.commit = AsyncMock()
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ctx = MagicMock()
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ctx.__aenter__ = AsyncMock(return_value=session)
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ctx.__aexit__ = AsyncMock(return_value=False)
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return session, ctx
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async def test_upsert_stores_one_versioned_row_per_chunk():
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from unittest.mock import AsyncMock, patch
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from scribe.services import embeddings as emb
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body = "\n\n".join(
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f"## Section {i}\n\n{_long_section(f'sec-{i}')}" for i in range(6)
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)
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chunks = chunk_document("T", body)
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assert len(chunks) > 1
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session, ctx = _session_ctx()
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with (
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patch.object(emb, "async_session", return_value=ctx),
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patch.object(
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emb, "get_embeddings",
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AsyncMock(return_value=[[0.0] * 384 for _ in chunks]),
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),
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):
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await emb.upsert_note_embedding(7, 42, "T", body)
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rows = [call.args[0] for call in session.add.call_args_list]
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assert [r.chunk_index for r in rows] == list(range(len(chunks)))
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assert [r.chunk_text for r in rows] == chunks
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assert {r.chunker_version for r in rows} == {emb.CHUNKER_VERSION}
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assert {r.user_id for r in rows} == {42}
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session.execute.assert_awaited() # the delete that makes replacement atomic
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async def test_upsert_of_an_emptied_record_clears_rows_instead_of_embedding():
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"""An empty embedding is worse than none, and a STALE one is worse than
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that — a record emptied of content must stop being findable by what it no
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longer says."""
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from unittest.mock import patch
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from scribe.services import embeddings as emb
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session, ctx = _session_ctx()
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with (
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patch.object(emb, "async_session", return_value=ctx),
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patch.object(emb, "get_embeddings") as embedder,
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):
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await emb.upsert_note_embedding(7, 42, "", "")
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embedder.assert_not_called()
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session.execute.assert_awaited() # the delete
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session.add.assert_not_called()
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session.commit.assert_awaited()
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async def test_backfill_reembeds_notes_with_a_stale_chunker_version():
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"""The reason chunker_version exists: a shape change becomes a version
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bump that re-embeds exactly the stale notes, instead of another 0077-style
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table wipe. Only rows AT the current version count as done."""
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from unittest.mock import AsyncMock, MagicMock, patch
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from scribe.services import embeddings as emb
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current_rows = MagicMock()
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current_rows.fetchall.return_value = [(1,)] # note 1 is current
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note_rows = MagicMock()
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note_rows.fetchall.return_value = [
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(1, 42, "current", "body"),
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(2, 42, "stale-version", "body"),
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]
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session, ctx = _session_ctx()
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session.execute = AsyncMock(side_effect=[current_rows, note_rows])
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with (
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patch.object(emb, "async_session", return_value=ctx),
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patch.object(emb, "upsert_note_embedding", AsyncMock()) as upsert,
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patch.object(emb.asyncio, "sleep", AsyncMock()),
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):
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await emb.backfill_note_embeddings()
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embedded = [call.args[0] for call in upsert.call_args_list]
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assert embedded == [2], "only the stale note is re-embedded"
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